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ABSTRACTThe ever-increasing demand for immediate access to information means interpreters and translators are increasingly using, and relying on, digital technology in their work. In the migratory context, machine translation (MT) and post-editing (PE) have the potential to greatly increase the efficiency of public service interpreting and translation (PSIT), which is currently experiencing huge demand. This article describes and evaluates the implementation of a module focused on MT and PE within a postgraduate PSIT programme at a Spanish university. A mixed-methods methodology was used to collect both quantitative data (via a questionnaire) and qualitative data (via a reflective essay) from a group of 42 students during the 2020–2021 academic year. The results show that students were satisfied overall with both the content of the module and its implementation. However, they also felt that the module needed to be better integrated within the postgraduate PSIT programme as a whole in order to fully prepare them for their professional careers.

Anthraquinone has been linked to potential adverse effects on human health and the environment. The most commonly employed methods for the analysis of coffee and tea cause the extraction of matrix interferents such as the methylxanthines caffeine and theobromine, which hinder the analysis of anthraquinone. A new manual extraction method – using ethyl acetate as the extraction solvent with a dispersive solid-phase extraction clean-up step based on primary–secondary amines – has been developed. The new developed method allows for the quantitation of anthraquinone at 5 μg kg−1concentration levels, four times lower than the current maximum residue limit for coffee and tea in the European Union (20 μg kg−1). Alongside, a new automated extraction method has also been developed. Finally, a pilot monitoring programme of 90 coffee and tea samples from several countries within the European Union has been performed, in which anthraquinone has been detected in a concentration range of 5.1–18.8 μg kg−1in 32% of the monitored samples, below the current 20 μg kg−1maximum residue limit, and in 48% of the monitored tea samples, revealing the need for including anthraquinone in a more extensive monitoring programme of tea.

This study describes an evaluation of full-scan MS analysis combined with target and non-target MS2 acquisition along with targeted processing for pesticides in fruit and vegetables. Two databases were used comprising priority compounds (target acquisition) and less frequently detected compounds (non-target acquisition). Full-scan MS data were used for detection and quantitation, whereas MS2 data were used for identification. Target MS2 (data-dependent MS2) data were acquired for 166 pesticides with known retention times. Non-target MS2 (all-ion fragmentation MS2) data were obtained against a database containing 101 pesticides without retention times. At the level of 0.01 mg kg−1, selected target pesticides were identified in 99% of the cases in tomato (the best case) and in 92% of the cases in leek (the worst case). Peak area repeatability (RSD < 20%) at 0.01 mg kg−1was satisfactory (99% of compounds in tomato and 90% in leek). In the case of non-target compounds (searched without retention times), the numbers of false-positive and false-negative results were determined. A total of seventy-two real samples were used to determine the false positives. The database search was carried out considering only the full-scan MS ion, the full-scan MS ion and one MS2 fragment, and the full-scan MS ion and two MS2 fragments. In the first case, 297 false positives were found, whereas in the second case, 7, and in the third case, 4 false positives were found. Analogical database searches were carried out for five spiked matrices to determine the false negatives. At the level of 0.01 mg kg−1, three ions (one in full-scan MS and two in MS2) were found for 96% of the compounds in tomato and lettuce (the best cases) and 75% of the compounds in leek (the worst case). Two ions (one in full-scan MS and one in MS2) were detected for 100% of the pesticides in lettuce and for 95% of the pesticides in leek. These results clearly show the high analytical performance of the applied workflow, with important advantages derived by increasing the analytical scope for qualitative screening. The approach presented in this study combines the advantages of target and non-target MS2 analysis.